Identifying P phase arrival of weak events: The Akaike Information Criterion picking application based on the Empirical Mode Decomposition

Seismic P phase arrival picking of weak events is a difficult problem in seismology. The algorithm proposed in this research is based on Empirical Mode Decomposition (EMD) and on the Akaike Information Criterion (AIC) picker. It has been called the EMD-AIC picker. The EMD is a self-adaptive signal decomposition method that not only improves Signal to Noise Ratio (SNR) but also retains P phase arrival information. Then, P phase arrival picking has been determined by applying the AIC picker to the selected main Intrinsic Mode Functions (IMFs). The performance of the EMD-AIC picker has been evaluated on the basis of 1938 micro-seismic signals from the Yongshaba mine (China). The P phases identified by this algorithm have been compared with manual pickings. The evaluation results confirm that the EMD-AIC pickings are highly accurate for the majority of the micro-seismograms. Moreover, the pickings are independent of the kind of noise. Finally, the results obtained by this algorithm have been compared to the wavelet based Discrete Wavelet Transform (DWT)-AIC pickings. This comparison has demonstrated that the EMD-AIC picking method has a better picking accuracy than the DWT-AIC picking method, thus showing this method's reliability and potential. An EMD-AIC picker has been proposed to identify micro-seismic P phase arrival.The EMD-AIC picking method works efficiently for the majority of identifications.The EMD-AIC method has a better picking accuracy than the DWT-AIC pickings.

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